Robotics and Autonomy in Manufacturingfiles.messe.de/abstracts/83061_uni_2504_Schneider.pdf ·...

Robotics and Autonomy in Manufacturing

Stan Schneider, PhD

RTI CEO

IIC Steering Committee Vice Chair

©2018 Real-Time Innovations, Inc. Permission granted to distribute unmodified pdf.

The smart machine era will be the most disruptive in the history

The Industrial IoT Disruption Across Industries


The real value is a common architecture that connects sensor to cloud, interoperates between vendors, and spans industries

You don’t compete against competitors. You compete against market transitions.

– John Chambers

Connectivity Technologies


The Industrial Internet Connectivity Framework

• The industry’s only detailed analysis of IIoT Connectivity Technologies

• Architecture

• Assessment

• Standards– DDS– OPC UA– OneM2M– HTTP– MQTT– CoAP

• Examples & selection guidance

• Years of work by many architects across industries, standards, & technologies


Released Feb 28, 2017

Connectivity Technologies Don’t Overlap!


System Aspect Example User Approach Standard

Software Integration & Autonomy

Software Architect integrating components

Data-centric DDS

Device interchangeability

Device manufacturer sellingdevices to technicians

Device-centric OPC-UA

Web & Mobile User I/F App builder supportingback-end services

RESTful Web services/HTTP

ICT integration Wide-area wireless telecom integrator

Common services layer

oneM2M

Data Centric is the Opposite of OO


Object Oriented• Encapsulate data• Expose methods• Sequential execution

Data Centric• Encapsulate methods• Expose data• Parallel updates

ExplicitShared

Data Model

Users and Applications are Very Different!

You are a software architect. You:

• Manage & integrate software development teams

• Design & control architecture & data model

• Face challenges in defining software module interfaces, implementing redundancy, complex data flow

You are a device manufacturer. You:

• Build a device for many applications

• Do not control the installation data architecture

• Face challenges of device vendor interoperability, users who are not software experts


OPC UA

Device Integration for Vendor Interoperability


OPC UA Devices Provide Vendor Interoperability


OPC UA

• Device-Centric Object-Oriented Framework– Device models for common devices

– Integrate devices into workcells

– Client-server architecture

– Browsable address space

– New simple UDP pub-sub


Motor Starter 01

Configuration

Control Function Local Operation

Multifunction Input DI0

ParameterSet Motor Parameters

Motor Current Low

Motor Current High

Service Info

Number of Starts

Motor Starter 01

Parameter Set

Control Function

Local Operation

Configuration

Multifunction Input DIO

Motor Current Low

Motor Current High

Number of Starts

Motor Current Low

Motor Current High

Service Info

Address Space

Device Integration

• Challenges– Interoperate between

vendors– Assembled by engineers

or technicians

• Components– Devices– Reusable software

products (e.g. HMI)

• Interfaces– Standard device models– Dynamic address space

rollup– Read/write variables


Device A

Device B

HMI

Historian

Device E

• Standard device types• Read/write variables

The DDS Databus

Software Integration for Autonomous Control



DDS Autonomy Applications Span the IIoT

Autonomous Systems Challenges

• Manage complex data flow and state• Ease system integration• Ensure reliable data availability• Guarantee real-time response• Allow any network• Build in security from the start• Make deployment flexible• Ease safety certification• Adapt Intelligence• Connect with Cloud Systems


RTI founded from Stanford Aerospace Robotics Lab

Integrate Complex Software for Real-Time Distributed

Control

Autonomy Dataflow Challenge

• Autonomy combines:– Volume– Frequency– Latency– Reliability– Destination

• A single abstraction that can handle all greatly simplifies the system


Cameras

Lidar

Radar

GPS

Control Cmd

Error

Data Source

Video Stream

Data List

Point cloud

Bin data struct

Bin data struct

Text String

Data Type Data Volume Data Frequency

Enable Autonomy


Cloud Services

Sensing

Planning

Radar, LIDAR Vehicle Platform Navigation

Error Management

Visualization

Situation AnalysisSituation Awareness

Vision FusionCameras, LIDAR,

Radar …

Data Fusion

LoggingVehicle Control

Localization

Databus

Traffic Maps

DatabusCars Now Compete on Software

The DDS Databus


Application

Application

Message centricClient/ServerRemote ObjectsPublish-subscribeSOA

DDS is the standard that defines a databus

Data-centric technology connects applications to

the data, not to each other

Application

Application

Data

Application

DDS “Data Everywhere” Abstraction

• Doesn’t actually send all data…

• Every application gets everything it needs, when it needs it– Applications declare

needs and capabilities– Databus delivers data

• Applications interface only to data– Every app speaks its own

language– Databus maps language,

CPU, OS, transport

• No servers

• Fast, reliable, scalable


Shared Global Data Space

DDS DataBus

DataTopicTypeQoS

DataTopicTypeQoS

Data

TopicTypeQoS

Naturally parallel virtual shared memory

Why a Databus? Software Decoupling.

• Flow: discovery, rates, reliability uncoupled– Any network, any transport– Full QoS control for every flow

• Space: services live anywhere– Cloud, fog, devices– Move them transparently– Controlled, natural redundancy

• Time: robust system operations– No dependency on startup sequence– Participants come & go at will– Matches evolving schema


Since Software Integration is All About The Data…

• Decoupled subsystems work independently

• Data-centric sharing lets them cooperate


DDS Underlies the ROS v2 Software Stack

OS Linux

ROS abstract middleware layer (RMW) (C API)

ROS client library (rcl)

OS X Windows

DDS Databus

Your OS here

C++ client library Python client libraryC client library

Userland code


Software Integration

• Challenges– Interface many software

teams– Interoperate between

software modules– Version matching

• Components– Custom software – AIs, libraries

• Interfaces– Global data abstraction– Dataflow control– Common system data

model


• Custom data model• Dynamic types• Dataflow control

Putting Them Together

Integrating OPC UA and DDS


IIC Connectivity Core Standards Architecture

• Connectivity Core Standards– Provide syntactic

interoperability– Stable, deployed, open

standard– Standard Core Gateways

to all other CCS

• Domain-Specific Connectivity Technologies– Connect via non-

standard gateway to any connectivity core standard

Few Core StandardsStandard Core

Gateways

Many domain technologies


Shared Global Data Space

DDS DataBus

Data1TopicTypeQoS

Data3Topic

TypeQoS

Data2TopicTypeQoS

OPC UA Pubsub

OPC UA-DDS Gateway

Device A

Device B

HMI

Historian

Device E

• Standard device types• Read/write variables

• Custom data model• Dynamic types• Dataflow control

Software integration

Device Integration

Conceptual Architecture Integration Approach


Provide transparent interoperability between existing DDS and OPC UA applications.

OPC-UA/DDS Gateway Standard


OMG mars/2018-02-01

OPC UA → DDS

• To allow DDS applications to access, subscribe, read, and manage information from OPC UA, this side of the gateway has: – DomainParticipants and a set of endpoints (DataReaders and DataWriters) to interact with DDS applications.– An OPC UA Client (or a set of OPC UA Clients) to connect to OPC UA Servers that provide the information.

• Different building blocks allow DDS applications to perform different tasks:– OPC UA Type System Mapping to DDS– OPC UA Service Invocation from DDS– OPC UA Subscription from DDS


DDS → OPC UA

• To allow OPC UA clients to access, subscribe, read, and manage information from DDS, this side of the gateway has: – An OPC UA Server that exposes a portion of the information available in the DDS Global Data Space.– DomainParticipants, Publishers, Subscribers, DataReaders, and DataWriters endpoints to interact with

DDS applications.

• Different building blocks allow OPC UA clients to perform different tasks:– DDS Type System Mapping to OPC UA– DDS Global Data Space Representation in OPC UA


Combine Software and Device Integration

Fog Domain (Edge)

OPCUA

DDS

Gateway

DDS

OPCUA

OPCUA

DDS

DDS

OPCUA

Gateway

DDS

OPCUA

OPCUA

DDS

Higher Domains

Integrate Autonomy Software With DDS

Connect Interoperable Devices with OPC UA

Device A

Device B

HMI

Historian

Device E


OPC UA/DDS Gateway Demo!


Further Information

• Industrial Internet Connectivity Framework (IICF): www.iiconsortium.org/IICF.htm

• Guide to IIoT Connectivity: http://www.iiconsortium.org/journal-of-innovation.htm

• eBook coming in April; register for it online: www.rti.com/eBook


http://www.iiconsortium.org/IICF.htm

http://www.iiconsortium.org/journal-of-innovation.htm

http://www.rti.com/eBook

Connect!!

• [email protected]@RTIStan

LinkedIn: Stan Schneiderhttps://www.linkedin.com/in/stan-schneider-102466/

• Bio– CEO Real-Time Innovations, Inc

– IIC Steering Committee Vice Chair

• Past Chair, Testbed Subcommittee

• Co-chair Ecosystem Task Group

– Advisory Board, IoT SWC– Top-10 Global IIoT Influencer

– PhD, EE/CS, Stanford


https://www.linkedin.com/in/stan-schneider-102466/

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